期刊
COMPUTERS AND ELECTRONICS IN AGRICULTURE
卷 172, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.compag.2020.105305
关键词
Precision farming; Reduced inputs; Technology adoption; Small-holder agriculture; Agricultural service providers; Structural equation modelling
资金
- UK-China Research and Innovation Partnership Fund (Newton Programme: PAFiC-Precision Agriculture for Family-farms in China project, National Natural Science Foundation of China (NSFC) [61661136003]
- Science and Technology Facilities Council (STFC) of United Kingdom [ST/N006801/1]
- National Key Research and Development Program of China [2017YFE0122500]
- China Scholarship Council (CSC) [201706410040]
- STFC [ST/N006801/1] Funding Source: UKRI
Precision agriculture has the potential to deliver improved and more sustainable food production. Despite the various Chinese policy initiatives to strengthen national food security, there is evidence that the adoption of precision agriculture technologies in China has been much lower when compared to other developed agricultural economies. This study therefore aims to explore factors that determine Chinese farmers' adoption of precision agriculture technologies in cropping systems and to provide recommendations on technology promotion in the future. The current status of precision agriculture adoption by smallholder farmers within crop farming systems in the North China Plain was explored. An integrated model of Adapted Unified Theory of Acceptance and Usage of Technology (AUT(2)) was developed to explain individual farmers' intention to adopt precision agriculture. 456 surveys were conducted via face to face interviews in the North China Plain and structural equation modelling analysis was used to estimate the proposed AUT(2) model. The results showed that perceived need for technology characteristics (PNTC), perceived benefits, perception of the efficacy of facilitating conditions and perceived risks of adoption have significant impacts on farmers' intention to adopt precision agriculture. The facilitating conditions (e.g. knowledge, resources and access to consultant services) were the best predictor improving Chinese farmers' willingness to adopt these technologies. Policy makers and service providers need to consider these factors in the promotion of technologies.
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